The ability to detect a driver's behavior can provide many advantages, such as being able to detect patterns, tendencies, and habits. Such information is useful for allowing a driver or a third-party to make inferences about a driver's risk factors and allowing drivers to modify driving behavior when needed. However, despite technological advancements, current technologies still lack the ability to accurately detect a driver's behavior and identify patterns and changes in the driver's behavior. Accordingly, there remains a need for improved techniques for detecting a driver's behavior accurately.
Thus, a need still remains for a computing system with a driver behavior detection mechanism. In view of the ever-increasing commercial competitive pressures, along with growing consumer expectations and the diminishing opportunities for meaningful product differentiation in the marketplace, it is increasingly critical that answers be found to these problems. Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems
Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.